Colour quantisation using self-organizing migrating algorithm

Abstract

Colour quantisation is a common image processing technique to reduce the number of distinct colours in an image. Selecting these colour, which comprise a colour palette, is a challenging task since they determine the resulting image quality. In this paper, we propose a novel colour quantisation algorithm based on the Self-Organizing Migrating Algorithm (SOMA), in particular, SOMA Team To Team Adaptive (SOMA T3A), a recent variant of SOMA. SOMA T3A works, iteratively in three phases, namely organization, migration, and update, and performs adaptive parameter definition. Migrants are selected from the population and move towards a leader during the organization process. Experimental results on a benchmark set of images show excellent colour quantisation performance and our approach to outperform several conventional and soft-computing-based colour quantisation algorithms.